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The divide-and-conquer strategy is a learning algorithm for inducing Decision Trees. Its name reflects its key idea, which is to successively partition the dataset into smaller sets (the divide part) and recursively call itself on each subset (the conquer part). It should not be confused with the separate-and-conquer strategy which is used in the Covering Algorithm for rule learning.
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Fürnkranz, J. (2017). Divide-and-Conquer Learning. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_303
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_303
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Publisher Name: Springer, Boston, MA
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